Kafka / Flink Engineer

Job Title: Kafka / Flink Engineer

Location: NYC, NY || Fortmill, SC

Priority: Critical

Job Description:
We are looking for a Kafka / Flink Engineer to design, build, and support real-time streaming data platforms. The ideal candidate will have strong hands-on experience with Apache Kafka and Apache Flink, and a solid understanding of distributed systems, stream processing, and data pipelines in production environments.

Key Responsibilities:

• Design, develop, and maintain real-time data streaming solutions using Apache Kafka and Apache Flink
• Build and optimize Kafka producers, consumers, topics, and stream processing applications
• Develop stateful and stateless Flink jobs for real-time analytics and event processing
• Ensure high availability, fault tolerance, and scalability of streaming platforms
• Monitor, troubleshoot, and resolve performance and reliability issues in production
• Collaborate with data engineers, platform teams, and application teams to integrate streaming solutions
• Implement data quality, security, and governance best practices
• Participate in code reviews, design discussions, and technical documentation

Required Skills & Qualifications:

• Strong hands-on experience with Apache Kafka (Kafka Streams, Connect, Schema Registry)
• Solid experience with Apache Flink for real-time stream processing
• Strong programming skills in Java or Scala (Python is a plus)
• Experience working with distributed systems and event-driven architectures
• Knowledge of message serialization formats (Avro, Protobuf, JSON)
• Experience with monitoring and logging tools for streaming systems
• Good understanding of data modeling and streaming data patterns

Preferred / Nice to Have:

• Experience with cloud platforms (AWS, Azure, or Google Cloud Platform)
• Knowledge of containerization and orchestration (Docker, Kubernetes)
• Experience with CI/CD pipelines for data platforms
• Exposure to other streaming tools such as Spark Streaming or Pulsar
• Understanding of security, authentication, and authorization in Kafka ecosystems